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OBJECTIVES: Nonconventional ventilators (NCVs), defined here as transport ventilators and certain noninvasive positive pressure devices, were used extensively as crisis-time ventilators for intubated patients with COVID-19. We assessed whether there was an association between the use of NCV and higher mortality, independent of other factors. DESIGN: This is a multicenter retrospective observational study. SETTING: The sample was recruited from a single healthcare system in New York. The recruitment period spanned from March 1, 2020, to April 30, 2020. PATIENTS: The sample includes patients who were intubated for COVID-19 acute respiratory distress syndrome (ARDS). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was 28-day in-hospital mortality. Multivariable logistic regression was used to derive the odds of mortality among patients managed exclusively with NCV throughout their ventilation period compared with the remainder of the sample while adjusting for other factors. A secondary analysis was also done, in which the mortality of a subset of the sample exclusively ventilated with NCV was compared with that of a propensity score-matched subset of the control group. Exclusive use of NCV was associated with a higher 28-day in-hospital mortality while adjusting for confounders in the regression analysis (odds ratio, 1.41; 95% CI [1.07-1.86]). In the propensity score matching analysis, the mortality of patients exclusively ventilated with NCV was 68.9%, and that of the control was 60.7% ( p = 0.02). CONCLUSIONS: Use of NCV was associated with increased mortality among patients with COVID-19 ARDS. More lives may be saved during future ventilator shortages if more full-feature ICU ventilators, rather than NCVs, are reserved in national and local stockpiles.
Subject(s)
COVID-19 , Hospital Mortality , Respiratory Distress Syndrome , Ventilators, Mechanical , Humans , COVID-19/therapy , COVID-19/mortality , Male , Female , Retrospective Studies , Middle Aged , Aged , Respiratory Distress Syndrome/therapy , Respiratory Distress Syndrome/mortality , Ventilators, Mechanical/supply & distribution , Ventilators, Mechanical/statistics & numerical data , New York/epidemiology , Respiration, Artificial/statistics & numerical dataABSTRACT
BACKGROUND: Classifying sphenoid pneumatisation is an important but often overlooked task in reporting sinus CT scans. Artificial intelligence (AI) and one of its key methods, convolutional neural networks (CNNs), can create algorithms that can learn from data without being programmed with explicit rules and have shown utility in radiological image classification. OBJECTIVE: To determine if a trained CNN can accurately classify sphenoid sinus pneumatisation on CT sinus imaging. METHODS: Sagittal slices through the natural ostium of the sphenoid sinus were extracted from retrospectively collected bone-window CT scans of the paranasal sinuses for consecutive patients over 6 years. Two blinded Otolaryngology residents reviewed each image and classified the sphenoid sinus pneumatisation as either conchal, presellar or sellar. An AI algorithm was developed using the Microsoft Azure Custom Vision deep learning platform to classify the pattern of pneumatisation. RESULTS: Seven hundred eighty images from 400 patients were used to train the algorithm, which was then tested on a further 118 images from 62 patients. The algorithm achieved an accuracy of 93.2% (95% confidence interval [CI] 87.1-97.0), 87.3% (95% CI 79.9-92.7) and 85.6% (95% CI 78.0-91.4) in correctly identifying conchal, presellar and sellar sphenoid pneumatisation, respectively. The overall weighted accuracy of the CNN was 85.9%. CONCLUSION: The CNN described demonstrated a moderately accurate classification of sphenoid pneumatisation subtypes on CT scans. The use of CNN-based assistive tools may enable surgeons to achieve safer operative planning through routine automated reporting allowing greater resources to be directed towards the identification of pathology.
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OBJECTIVES: To summarise the accuracy of artificial intelligence (AI) computer vision algorithms to classify ear disease from otoscopy. DESIGN: Systematic review and meta-analysis. METHODS: Using the PRISMA guidelines, nine online databases were searched for articles that used AI computer vision algorithms developed from various methods (convolutional neural networks, artificial neural networks, support vector machines, decision trees and k-nearest neighbours) to classify otoscopic images. Diagnostic classes of interest: normal tympanic membrane, acute otitis media (AOM), otitis media with effusion (OME), chronic otitis media (COM) with or without perforation, cholesteatoma and canal obstruction. MAIN OUTCOME MEASURES: Accuracy to correctly classify otoscopic images compared to otolaryngologists (ground truth). The Quality Assessment of Diagnostic Accuracy Studies Version 2 tool was used to assess the quality of methodology and risk of bias. RESULTS: Thirty-nine articles were included. Algorithms achieved 90.7% (95%CI: 90.1-91.3%) accuracy to difference between normal or abnormal otoscopy images in 14 studies. The most common multiclassification algorithm (3 or more diagnostic classes) achieved 97.6% (95%CI: 97.3-97.9%) accuracy to differentiate between normal, AOM and OME in three studies. AI algorithms outperformed human assessors to classify otoscopy images achieving 93.4% (95%CI: 90.5-96.4%) versus 73.2% (95%CI: 67.9-78.5%) accuracy in three studies. Convolutional neural networks achieved the highest accuracy compared to other classification methods. CONCLUSION: AI can classify ear disease from otoscopy. A concerted effort is required to establish a comprehensive and reliable otoscopy database for algorithm training. An AI-supported otoscopy system may assist health care workers, trainees and primary care practitioners with less otology experience identify ear disease.
Subject(s)
Ear Diseases , Otitis Media with Effusion , Otitis Media , Artificial Intelligence , Humans , Otitis Media/diagnosis , Otitis Media with Effusion/diagnosis , Otoscopes , Otoscopy/methodsABSTRACT
BACKGROUND: Acute respiratory distress syndrome (ARDS) was first described in 1967, but its definition has evolved considerably since then. ARDS is defined as the onset of hypoxemia, tachypnea, and loss of lung compliance due to some stimulus. In the United States, the incidence of ARDS has been growing because it is being increasingly recognized. The incidence of ARDS has also gone up recently due to the COVID-19 pandemic. AREAS OF UNCERTAINTY: To date, there is no known one treatment for ARDS. Multiple studies have looked into various causes of ARDS, pathophysiology, and ventilation and management strategies. However, there is still considerable variability in the treatment and management of these patients from institution to institution. DATA SOURCES: A literature search was conducted through PubMed and Google Scholar. Publications describing the epidemiology, diagnostic criteria, pathophysiology, and treatment were included in this review. RESULTS: The definition of ARDS has evolved over the years. The most recent and agreed upon diagnostic criteria are based on the Berlin criteria for ARDS. Management of patients with ARDS includes low tidal volume ventilation, prone ventilation, paralysis in certain patient populations, and perhaps extracorporeal membrane oxygenation (ECMO). This also applies to patients with ARDS due to COVID-19. CONCLUSIONS: Patients with ARDS have a high mortality due to the incredibly complex disease process. Because of the complexity of ARDS, the management and treatment is equally as difficult. This article reviews some of the strategies used to date, including the role of ECMO, and includes some society recommendations. Further research must be done into which methods best guide lung ventilation in severe ARDS and patients on ECMO.
Subject(s)
COVID-19 , Respiratory Distress Syndrome , COVID-19/epidemiology , COVID-19/physiopathology , Disease Management , Humans , Respiratory Distress Syndrome/epidemiology , Respiratory Distress Syndrome/physiopathology , Respiratory Distress Syndrome/therapy , SARS-CoV-2ABSTRACT
Mesoporous ZSM-5 zeolites were obtained from microporous ZSM-5 by desilication using aqueous NaOH solutions, and their catalytic activity in the aromatization of ethanol was investigated in order to understand the effects of pore size, in the mesoporous region, on the product distribution and stability of the catalysts. Mesopores generally enhanced the selectivities towards aromatics and stability for aromatization. Mesopores with a maximum pore diameter of around 13 nm were the most effective in the aromatization process (especially for benzene and toluene), suggesting that pore-diameter optimization is necessary for efficient catalysis such as aromatization.
Subject(s)
Ethanol/chemistry , Hydrocarbons, Aromatic/chemical synthesis , Nanoparticles/chemistry , Nanoparticles/ultrastructure , Nanopores/ultrastructure , Zeolites/chemistry , Conservation of Energy Resources/methods , Materials Testing , Porosity , Silicon Dioxide/chemistryABSTRACT
The adsorptive removal of organoarsenic compounds such as p-arsanilic acid (ASA) and roxarsone (ROX) from water using metal-organic frameworks (MOFs) has been investigated for the first time. A MOF, iron benzenetricarboxylate (also called MIL-100-Fe) exhibits a much higher adsorption capacity for ASA and ROX than activated carbon, zeolite (HY), goethite, and other MOFs. The adsorption of ASA and ROX over MIL-100-Fe is also much more rapid than that over activated carbon. Moreover, the used MIL-100-Fe can be recycled by simply washing with acidic ethanol. Therefore, it is determined that a MOF such as MIL-100-Fe can be used to remove organoarsenic compounds from contaminated water because of its high adsorption capacity, rapid adsorption, and ready regeneration. Moreover, only one of three analogous MIL-100 species (MIL-100-Fe, rather than MIL-100-Al or MIL-100-Cr) can effectively remove the organoarsenic compounds. This selective and high adsorption over MIL-100-Fe, different from other analogous MIL-100 species, can be explained (through calculations) by the facile desorption of water from MIL-100-Fe as well as the large (absolute value) replacement energy (difference between the adsorption energies of the organoarsenic compounds and water) exhibited by MIL-100-Fe. A plausible adsorption/desorption mechanism is proposed based on the surface charge of the MOFs, FTIR results, calculations, and the reactivation results with respect to the solvents used in the experiments.
Subject(s)
Arsanilic Acid/chemistry , Organometallic Compounds/chemistry , Roxarsone/chemistry , Water Pollutants, Chemical/chemistry , Adsorption , Coordination Complexes/chemistry , Hydrogen-Ion Concentration , Ions/chemistry , Iron/chemistry , Metal-Organic Frameworks , Spectroscopy, Fourier Transform Infrared , Water PurificationABSTRACT
Acidic ionic-liquids (IL) supported on metal-organic frameworks (MOFs) have been shown to be beneficial for adsorptive desulfurization. A remarkable improvement in the adsorption capacity (ca. 71%) was observed in for ILs supported on MIL-101 compared with virgin MIL-101. The improved adsorptive performance might be explained by the acid-base interactions between the acidic ionic liquid and basic benzothiophene (BT). Moreover, from this study, it can be suggested that porous MOFs, supported with ionic liquids, may introduce a new class of highly porous adsorbents for the efficient adsorption of various compounds.
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OBJECTIVE: Quality and adequacy of the electrode neuron interface (ENI) is postulated to be a determining factor in affecting auditory outcomes after cochlear implantation. This study aims to review radiological parameters affecting ENI, including angular insertion (AngI), wrapping factor (WF), scalar translocation (ScaT), and electrode-modiolar distance (EMD) and their effect on auditory outcomes. DATABASES REVIEWED: PubMed, MEDLINE, Embase, Scopus, OpenGrey, and Google Scholar from inception to 01 September 2022. METHODS: Inclusion criteria were (i) all humans with any cochlear implant (CI); (ii) postoperative cross-sectional imaging with electrode position factors of AngI, ScaT, EMD, and/or WF; and (iii) associated auditory outcomes. Search was restricted to English-language literature. Two independent reviewers performed title and abstract screening, data extraction, and ROBINS-I risk of bias assessment. Formal statistical analysis not performed due to data heterogeneity. PROSPERO (CRD42022359198). RESULTS: Thirty-one studies (n = 2,887 patients, 3,091 electrodes) underwent qualitative synthesis. Higher AngI (n = 1921 patients) demonstrated positive correlation in 11 studies, no correlation in eight studies, and negative correlation in four studies. ScaT (n = 2,115 patients) demonstrated negative correlation in 12 studies, none in six studies, and one unclear correlation. Larger EMD (n = 240 patients) showed negative correlation in two studies, no correlation in one, and unclear correlation in one study. Smaller WF (n = 369 patients) demonstrated no correlation in three studies and positive correlation in one study. CONCLUSIONS: Our study finds variable reported relationship between AngI and auditory outcomes. CI electrodes with a ScaT or larger EMD are more likely to exhibit poorer outcomes, and WF does not correlate with outcomes.
Subject(s)
Cochlear Implantation , Cochlear Implants , Humans , Cochlear Implantation/methods , Cochlear Implants/adverse effects , Cochlea/surgeryABSTRACT
OBJECTIVE: This review aims to quantify the pooled functional gain (FG) in different types of hearing loss with the transcutaneous hearing device, Osia (Cochlear, Sydney, Australia) in comparison with the unaided state. Secondary outcomes are patient-reported outcomes measures (PROMs) and complication rates. DATA SOURCES: Medline, Embase, SCOPUS, Cochrane CENTRAL, PROSPERO and Cochrane Library. REVIEW METHODS: Systematic review and meta-analysis of indexed search terms relating to "Osia," "Osseointegration," "Cochlear Implant," and "Bone-Anchored Prosthesis" was performed from database inception to September 20, 2022. RESULTS: Of the 168 studies identified, 14 studies with 15 patient cohorts (n = 314) met inclusion criteria for meta-analysis. Pooled overall mean FG for all types of hearing loss was 35.0 dB sound pressure level (SPL) (95% confidence interval [CI] 29.12-40.97) compared against unaided hearing. Pooled FG for conductive/mixed hearing loss was 37.7 dB SPL (95% CI 26.1-49.3). Pooled single-sided deafness (SSD) FG could not be calculated due to the small patient cohort for whom SSD data was reported. There is a trend toward improvements in speech receptiveness threshold, signal to noise ratio, and some PROMs compared with baseline hearing. Early complication rates demonstrate risks similar to other transcutaneous implants, with a low predicted explantation (0.11%, 95% CI 0.00%-1.90%) and wound infection rate (1.92% [95% CI 0.00%-6.17%]). No articles directly comparing transcutaneous devices were identified. CONCLUSION: The Osia devices demonstrate clear audiologic benefits and a good safety profile for the included patient population. Our study results indicate that frequency-specific gain, PROMs, and the audiological benefit in single-sided deafness may be areas for future prospective research. Laryngoscope, 134:1531-1539, 2024.
Subject(s)
Cochlear Implants , Deafness , Hearing Aids , Hearing Loss , Speech Perception , Humans , Bone Conduction , Hearing Loss, Conductive/surgery , Hearing Loss/surgery , Treatment OutcomeABSTRACT
OBJECTIVE: Carcinoma ex pleomorphic adenoma (CXPA) is a rare malignant salivary gland tumor. Although multiple reviews have been published on salivary gland malignancies, it has been a decade since the last dedicated systematic review pertaining to CXPA alone was published. This study examines molecular factors in CXPA diagnosis. DATA SOURCES: MEDLINE, CINAHL, Embase, Scopus, Web of Science (BIOSIS), Cochrane CENTRAL, Health Collection (Informit), OpenDOAR, and GreyNet International. REVIEW METHODS: Systematic review and meta-analysis from inception to October 31, 2022 for all English language studies pertaining to "carcinoma ex pleomorphic adenoma." Predicted incidence of each biomarker was calculated with meta-analysis. Comparison against pleomorphic adenoma (PA) and salivary duct carcinoma (SDC) when reported within the same study are performed. Risk of bias performed with JBI tool for prevalence studies. RESULTS: Of 19151 unique studies undergoing abstract screening, 55 studies (n = 1322 patients) underwent data analysis. Biomarkers with >3 studies were p53, HER2, AR, EGFR, PLAG1, ERBB, ER, PR, HMGA2, p16, p63, a-SMA, RAS, PTEN, PDL1, BRAF, PIK3CA, and c-kit. Highest incidence was seen in AR, EGFR, p16, and p53. Significant differences were demonstrated compared with PA and SDC. There was high heterogeneity and overall high risk of bias within studies. CONCLUSION: Molecular factors are an area of interest in the diagnosis of CXPA. Our study results support examining CXPA as a discrete cohort in future targeted therapy trials. Laryngoscope, 134:1042-1053, 2024.
Subject(s)
Adenocarcinoma , Adenoma, Pleomorphic , Salivary Gland Neoplasms , Humans , Adenoma, Pleomorphic/diagnosis , Tumor Suppressor Protein p53 , Biomarkers, Tumor , Salivary Gland Neoplasms/pathology , ErbB ReceptorsABSTRACT
Adsorptive removal of bisphenol-A (BPA) using a MOF, Cr-benzenedicarboxylate (MIL-53), has been studied to understand the applicability of MOFs for the removal of hazardous endocrine disturbing chemicals from water. MIL-53 shows very fast adsorption in an hour and the adsorption capacity of MIL-53 is higher than that of activated carbon. Importantly, the adsorption of BPA over MIL-53 is very favorable especially at very low concentrations of BPA. Therefore, MOFs such as MIL-53 can be one of adsorbents that may be used in the adsorptive removal of BPA from contaminated water.
Subject(s)
Benzene/chemistry , Benzhydryl Compounds/isolation & purification , Chromium/chemistry , Dicarboxylic Acids/chemistry , Metals/chemistry , Organic Chemicals/chemistry , Phenols/isolation & purification , Water Pollutants, Chemical/isolation & purification , Adsorption , X-Ray DiffractionABSTRACT
Osteolipomas are a rare variant of lipomas. We present a case of osteolipoma of external audiotry canal in a 30 year old lady who presented with right sided ear fullness since 2 years. A well circumscribed mass was found arising from right bony external audiotry canal. Computed tomography revealed a calcified lesion measuring 9 × 7 mm in the cartilaginous portion of right external auditory canal. Diagnosis of Osteolipomas was made histologically and patient was treated with simple excision of the mass under local anaesthesia.
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BACKGROUND: Petrous temporal bone cone-beam computed tomography scans help aid diagnosis and accurate identification of key operative landmarks in temporal bone and mastoid surgery. Our primary objective was to determine the accuracy of using a deep learning convolutional neural network algorithm to augment identification of structures on petrous temporal bone cone-beam computed tomography. Our secondary objective was to compare the accuracy of convolutional neural network structure identification when trained by a senior versus junior clinician. METHODS: A total of 129 petrous temporal bone cone-beam computed tomography scans were obtained from an Australian public tertiary hospital. Key intraoperative landmarks were labeled in 68 scans using bounding boxes on axial and coronal slices at the level of the malleoincudal joint by an otolaryngology registrar and board-certified otolaryngologist. Automated structure identification was performed on axial and coronal slices of the remaining 61 scans using a convolutional neural network (Microsoft Custom Vision) trained using the labeled dataset. Convolutional neural network structure identification accuracy was manually verified by an otolaryngologist, and accuracy when trained by the registrar and otolaryngologist labeled datasets respectively was compared. RESULTS: The convolutional neural network was able to perform automated structure identification in petrous temporal bone cone-beam computed tomography scans with a high degree of accuracy in both axial (0.958) and coronal (0.924) slices (P < .001). Convolutional neural network accuracy was proportionate to the seniority of the training clinician in structures with features more difficult to distinguish on single slices such as the cochlea, vestibule, and carotid canal. CONCLUSION: Convolutional neural networks can perform automated structure identification in petrous temporal bone cone-beam computed tomography scans with a high degree of accuracy, with the performance being proportionate to the seniority of the training clinician. Training of the convolutional neural network by the most senior clinician is desirable to maximize the accuracy of the results.
Subject(s)
Deep Learning , Australia , Algorithms , Tomography, X-Ray Computed , Temporal Bone/diagnostic imaging , Image Processing, Computer-Assisted/methodsABSTRACT
INTRODUCTION: Convolutional neural networks (CNNs) represent a state-of-the-art methodological technique in AI and deep learning, and were specifically created for image classification and computer vision tasks. CNNs have been applied in radiology in a number of different disciplines, mostly outside otolaryngology, potentially due to a lack of familiarity with this technology within the otolaryngology community. CNNs have the potential to revolutionize clinical practice by reducing the time required to perform manual tasks. This literature search aims to present a comprehensive systematic review of the published literature with regard to CNNs and their utility to date in ENT radiology. METHODS: Data were extracted from a variety of databases including PubMED, Proquest, MEDLINE Open Knowledge Maps, and Gale OneFile Computer Science. Medical subject headings (MeSH) terms and keywords were used to extract related literature from each databases inception to October 2020. Inclusion criteria were studies where CNNs were used as the main intervention and CNNs focusing on radiology relevant to ENT. Titles and abstracts were reviewed followed by the contents. Once the final list of articles was obtained, their reference lists were also searched to identify further articles. RESULTS: Thirty articles were identified for inclusion in this study. Studies utilizing CNNs in most ENT subspecialties were identified. Studies utilized CNNs for a number of tasks including identification of structures, presence of pathology, and segmentation of tumors for radiotherapy planning. All studies reported a high degree of accuracy of CNNs in performing the chosen task. CONCLUSION: This study provides a better understanding of CNN methodology used in ENT radiology demonstrating a myriad of potential uses for this exciting technology including nodule and tumor identification, identification of anatomical variation, and segmentation of tumors. It is anticipated that this field will continue to evolve and these technologies and methodologies will become more entrenched in our everyday practice.
Subject(s)
Otolaryngology , Radiology , Humans , Neural Networks, Computer , RadiographyABSTRACT
BACKGROUND: Pneumatization of the mastoid process is variable and of significance to the operative surgeon. Surgical approaches to the temporal bone require an understanding of pneumatization and its implications for surgical access. This study aims to determine the feasibility of using deep learning convolutional neural network algorithms to classify pneumatization of the mastoid process. METHODS: De-identified petrous temporal bone images were acquired from a tertiary hospital radiology picture archiving and communication system. A binary classification mode in the pretrained convolutional neural network was used to investigate the utility of convolutional neural networks in temporal bone imaging. False positive and negative images were reanalyzed by the investigators and qualitatively assessed to consider reasons for inaccuracy. RESULTS: The overall accuracy of the model was 0.954. At a probability threshold of 65%, the sensitivity of the model was 0.860 (95% CI 0.783-0.934) and the specificity was 0.989 (95% CI 0.960-0.999). The positive predictive value was 0.973 (95% CI 0.904-0.993) and the negative predictive value was 0.935 (95% CI 0.901-0.965). The false positive rate was 0.006. The F1 number was 0.926 demonstrating a high accuracy for the model. CONCLUSION: The temporal bone is a complex anatomical region of interest to otolaryngologists. Surgical planning requires high-resolution computed tomography scans, the interpretation of which can be augmented with machine learning. This initial study demonstrates the feasibility of utilizing machine learning algorithms to discriminate anatomical variation with a high degree of accuracy. It is hoped this will lead to further investigation regarding more complex anatomical structures in the temporal bone.
Subject(s)
Mastoid , Temporal Bone , Mastoid/diagnostic imaging , Temporal Bone/diagnostic imaging , Tomography, X-Ray Computed , Algorithms , ComputersABSTRACT
INTRODUCTION: Telehealth programs are important to deliver otolaryngology services for Aboriginal and Torres Strait Islander children living in rural and remote areas, where distance and access to specialists is a critical factor. OBJECTIVE: To evaluate the inter-rater agreement and value of increasing levels of clinical data (otoscopy with or without audiometry and in-field nurse impressions) to diagnose otitis media using a telehealth approach. DESIGN: Blinded, inter-rater reliability study. SETTING: Ear health and hearing assessments collected from a statewide telehealth program for Indigenous children living in rural and remote areas of Queensland, Australia. PARTICIPANTS: Thirteen board-certified otolaryngologists independently reviewed 80 telehealth assessments from 65 Indigenous children (mean age 5.7 ± 3.1 years, 33.8% female). INTERVENTIONS: Raters were provided increasing tiers of clinical data to assess concordance to the reference standard diagnosis: Tier A) otoscopic images alone, Tier B) otoscopic images plus tympanometry and category of hearing loss, and Tier C) as B plus static compliance, canal volume, pure-tone audiometry, and nurse impressions (otoscopic findings and presumed diagnosis). For each tier, raters were asked to determine which of the four diagnostic categories applied: normal aerated ear, acute otitis media (AOM), otitis media with effusion (OME), and chronic otitis media (COM). MAIN OUTCOME MEASURES: Proportion of agreement to the reference standard, prevalence-and-bias adjusted κ coefficients, mean difference in accuracy estimates between each tier of clinical data. RESULTS: Accuracy between raters and the reference standard increased with increased provision of clinical data (Tier A: 65% (95%CI: 63-68%), κ = 0.53 (95%CI: 0.48-0.57); Tier B: 77% (95%CI: 74-79%), 0.68 (95%CI: 0.65-0.72); C: 85% (95%CI: 82-87%), 0.79 (95%CI: 0.76-0.82)). Classification accuracy significantly improved between Tier A to B (mean difference:12%, p < 0.001) and between Tier B to C (mean difference: 8%, p < 0.001). The largest improvement in classification accuracy was observed between Tier A and C (mean difference: 20%, p < 0.001). Inter-rater agreement similarly improved with increasing provision of clinical data. CONCLUSIONS: There is substantial agreement between otolaryngologists to diagnose ear disease using electronically stored clinical data collected from telehealth assessments. The addition of audiometry, tympanometry and nurse impressions significantly improved expert accuracy and inter-rater agreement, compared to reviewing otoscopic images alone.
Subject(s)
Otitis Media , Telemedicine , Humans , Child , Female , Child, Preschool , Male , Otolaryngologists , Australian Aboriginal and Torres Strait Islander Peoples , Reproducibility of Results , Otitis Media/diagnosis , Audiometry, Pure-Tone , PrevalenceABSTRACT
The severe acute respiratory virus covariate-2 (SARS CoV-2) that causes Corona Virus Disease 2019 (COVID-19) has affected more than 194 million people worldwide and has attributed to or caused more than 4 million deaths. Acute kidney injury (AKI) is a common complication of COVID-19. Point of care ultrasonography (POCUS) can be a useful tool for the nephrologist. POCUS can be used to elucidate the cause of kidney disease and then also help to manage volume status. Here, we review pearls and pitfalls of using POCUS to manage COVID-19 associated AKI with special attention to kidney, lung, and cardiac ultrasound.
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OBJECTIVES: Carcinoma ex Pleomorphic Adenoma (CXPA) is a rare primary salivary gland malignancy, typically arising from a pre-existing pleomorphic adenoma. This systematic review examines prognostic factors affecting overall survival (OS) in major and minor salivary gland CXPA. MATERIALS AND METHODS: Systematic review of MEDLINE, Cochrane, Scopus, Web of Science, CINAHL, and Open Grey databases from inception to 31st March 2022 for all English-language literature pertaining to 'carcinoma ex pleomorphic adenoma'. All study types with greater than five patients with CXPA of the major and minor salivary glands were eligible for inclusion. RESULTS: Of 8143 studies, 39 studies (n = 5637 patients) meeting the inclusion criteria were included. Median OS at one, three, five, and ten years were 90.0 %, 72.0 %, 61.9 %, and 45.0 % respectively for all CXPA. Higher staging, T stage, nodal disease, grading, and invasion ≥ 1.5 mm had worse outcomes. Histological subtype, perineural invasion, and radiotherapy did not demonstrate a consistent trend. Three studies were evaluated to have high risk of bias, and was removed for sensitivity analysis. CONCLUSION: Survival outcomes worsen with time for all salivary gland CXPA. Further research on histopathological features and the utility of radiation therapy is required to guide patient selection for more aggressive treatment. REGISTRATION: CRD42021238544 (PROSPERO).
Subject(s)
Adenocarcinoma , Adenoma, Pleomorphic , Salivary Gland Neoplasms , Adenocarcinoma/pathology , Adenoma, Pleomorphic/pathology , Humans , Prognosis , Salivary Gland Neoplasms/pathology , Salivary Glands, Minor/pathologyABSTRACT
Adult growth hormone (GH) deficiency is rare and requires replacement with extrinsic/synthetic injection. GH hypersensitivity has been reported; specifically, atopic patients may develop rashes from somatotropin therapy. Allergic and non-allergic skin reactions to recombinant human GH are uncommon and infrequently reported. We describe a graded-dose challenge with intravenous Norditropin® in a 65-year-old atopic adult woman who developed a severe whole-body rash with Norditropin FlexPro® administration on several occasions but was negative on skin-prick testing to Norditropin® percutaneously and intradermally, but the patch testing was positive for gold and nickel. The patient was registered as a direct admission to the emergency room at a university hospital for a rapid antigen coronavirus disease 2019 (COVID-19) testing after having received two COVID-19 vaccinations and re-testing four months after vaccination. She was then directly admitted to a non-COVID-19 intensive care unit with direct bedside supervision by a registered nurse and a physician board certified in internal medicine, allergy/immunology, and pulmonary diseases. The patient brought a Norditropin® pen which our pharmacy team attached to a compatible syringe for dilutions. A graded dose challenge at a final dosage of 0.1 mL was performed and the patient was monitored for allergic and other adverse drug reactions, which did not occur. At the time of writing this case report, the patient has been maintained on Norditropin FlexPro® 0.1 mL and has not experienced any adverse reactions, including recurrent skin eruptions. The case presented is the first to describe a patient who successfully tolerated a graded dose challenge of an adult patient to GH replacement therapy (as Norditropin®) under supervision in an intensive care unit, whereas prior to reporting of this case, a graded dose challenge to GH replacement therapy had only been successfully performed in a child using another formulation of somatotropin (Humatrope®). Hence, this case lends support that graded dose challenge with somatotropin analogs may be considered for patients with isolated GH deficiency such as in the case presented here.
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Introduction Treatment with dexamethasone reduces mortality in patients with coronavirus disease 2019 (COVID-19) pneumonia requiring supplemental oxygen, but the optimal dose has not been determined. Objective To determine whether weight-based dexamethasone of 0.2 mg/kg is superior to 6 mg daily in reducing 28-day mortality in patients with COVID-19 and hypoxemia. Materials and methods A multicenter, open-label, randomized clinical trial was conducted between March 2021 and December 2021 at seven hospitals within Northwell Health. A total of 142 patients with confirmed COVID-19 and hypoxemia were included. Participants were randomized in a 1:1 ratio to dexamethasone 0.2 mg/kg intravenously daily (n = 70) or 6 mg daily (n = 72) for up to 10 days. Results There was no statistically significant difference in the primary outcome of 28-day all-cause mortality with deaths in 12 of 70 patients (17.14%) in the intervention group and 15 of 72 patients (20.83%) in the control group (p = 0.58). There were no statistically significant differences among the secondary outcomes. Conclusion In patients with COVID-19 and hypoxemia, the use of weight-based dexamethasone dosing was not superior to dexamethasone 6 mg in reducing all-cause mortality at 28 days. Clinical trial registration This study was registered under ClinicalTrials.gov (identifier: NCT04834375).